@GoogleDeepMind
The engine room of @Google. Building AI safely and responsibly to solve the world’s most complex problems. Join us: https://t.co/jUHQA27iBL
The biosecurity landscape is rapidly evolving. To stay ahead of future outbreaks, we’re partnering with @IsomorphicLabs to outline our approach to bioresilience. Here’s how we’re deploying frontier AI to build proactive defenses for global health → goo.gle/4wKHXk2
From proposing hypotheses to designing experiments, AI agents are starting to reshape scientific discovery. But the hardest part is testing these ideas in the real world. Our essay explores the growing validation bottleneck and outlines four priorities for policymakers and funders. → t.co/biz1QlHNtm
Here’s how we used the Predicting the Past Skill in Google @Antigravity to track down a Roman ring thief, map an ancient cult across Europe, and reconstruct the networks of people visiting a Greek oracle. 🧵
🔍 The ring thief of Aquae Sulis When given an 1,800 year old curse tablet, the Skill used Aeneas - our generative model for restoring, dating and placing ancient texts - to locate it in time and space. It also generated an explanation of why it made that prediction, acting as a piece of epigraphic commentary to the expert.
A model’s chain of thought acts like a scratch pad, offering a window into its reasoning. 📝 On the latest episode of our podcast, host @fryrsquared sits down with @NeelNanda5 to explore interpretability – the science of reverse engineering how neural networks learn and think. Timecodes: 00:00 Introduction 02:41 Motivation for interpretability research 04:01 Mechanistic interpretability 08:14 Chain of thought monitoring 18:14 Interpretability techniques 35:00 Auditing models for safety 48:53 What comes next for interpretability
Watch → goo.gle/4pxlGEh Spotify → goo.gle/4f89R2a Apple Podcasts → goo.gle/4fpWThL Or listen wherever you get your podcasts! 🎧
🏛️ We’re unveiling a new way to converse with the ancient world. By grounding Gemini directly in our expert models Aeneas and Ithaca, our Predicting the Past Skill in Google @antigravity lets historians study Greek and Latin texts using plain English. 🧵
Using AI for history analysis has 3 core challenges: 🔹 Creating custom analysis and visuals for every inscription. 🔹 Cross-source mapping to find large-scale patterns. 🔹 Utilizing advanced AI tools with no coding skills. Our Antigravity skill shifts all these complex workflows into plain English.
🏛️ We’re unveiling a new way to converse with the ancient world. By grounding Gemini directly in our expert models Aeneas and Ithaca, our Predicting the Past Skill in @GoogleAntigravity lets historians study Greek and Latin texts using plain English. 🧵
Using AI for history analysis has 3 core challenges: 🔹 Creating custom analysis and visuals for every inscription. 🔹 Cross-source mapping to find large-scale patterns. 🔹 Utilizing advanced AI tools with no coding skills. Our Antigravity skill shifts all these complex workflows into plain English.
As @Apptronik expands their Robot Park facility, our research partnership means real-world data collected by the latest Apollo 2 humanoid platform will help train and advance Gemini Robotics. 🤖 Find out more → goo.gle/4vOPwpO
We’re shipping 2 major releases: 🔘 Nano Banana 2 Lite: our fastest and cheapest Gemini Image model 🔘 Gemini Omni Flash: now available via the Gemini API and in @GoogleAIStudio to help developers generate and edit high-quality videos.
Nano Banana 2 Lite delivers text-to-image outputs in just 4 seconds. It’s designed for quicker ideation and workflows where speed and cost are the primary roadblocks.
Gemini 3.5 Flash now supports native computer use. This built-in tool lets developers build custom agents that can see and take action across browser, mobile, and desktop interfaces. Find out more → goo.gle/4f4sNQA
What happens when millions of AI agents start negotiating, transacting, and delegating to one another? @weballergy joined our podcast with @fryrsquared to explore the rise of agentic economies – and how we can diversify agent decision-making to avoid AI groupthink. Timecodes: 00:00 Intro 1:07 Defining AI agents 4:44 Agentic exploration in science and research 15:46 Delegation between agents 22:46 Agentic security and traps 29:31 Building an agentic economy 33:22 Cognitive monoculture 36:29 Distributed intelligence
Watch → goo.gle/4w7S3LM Spotify → goo.gle/4eFgIA9 Apple Podcasts → goo.gle/3Sn4ZyM Or listen wherever you get your podcasts! 🎧
Google DeepMind 🤝 @A24 We’re launching a research partnership with A24 to ensure the tools of the future are shaped by the creators who use them. Find out more → goo.gle/3QwvgKq
Instead of assuming AI will always do what we intend, we ask: what if it doesn't? That’s why we’ve developed our AI Control Roadmap: a framework for building and managing the advanced AI we deploy within Google. 🧵
Our data shows that the vast majority of issues don't stem from bad intent. They usually happen because an agent misinterprets a command or gets overly enthusiastic to achieve a goal. Understanding these nuances is critical for refining safety and security protocols. ⬇️
We’re working with @SciTechgovuk, @mhclg and @i_dot_ai on a new AI housing application planning prototype. 🏡 By cutting down the time spent on repetitive tasks, it could help planning officers focus their attention on complex projects and reduce processing times by up to 50%. → t.co/C2AdQOHPiX
Our Robotics Accelerator has launched with 15 startups helping shape the future of physical AI in Europe. 🤖 This three-month program will connect them with access to our AI stack, Gemini Robotics models and hands-on support from our teams. Meet the companies →
We’re teaming up @Palmeiras, the first football club to meaningfully build upon TacticAI: our AI system that can help simulate field scenarios and predict open play dynamics up to 8 seconds in advance. ⚽
To map the pitch, TacticAI uses graph neural networks - treating all 22 players as individual nodes and their physical interactions as connections. This allows the club's data science department to virtually drag and drop players to test different defensive setups in real time.
When millions of AI agents interact with each other, new collective behaviors can emerge. 🌐 Together with @schmidtsciences, @coop_ai, @ARIA_research and supported by @GoogleOrg, we’re launching a $10M research fund to help understand how AI systems behave as a group. →
In Sierra Leone, a surging student population is outpacing available teachers. Our latest research explores how AI can act as a partner to support educators in these environments – amplifying their reach without replacing their essential expertise and skills. 🧵
We evaluated AI’s impact by looking beyond test scores to behavioral shifts. Over eight weeks, results suggest students were using AI to understand concepts, not just find answers – with Gemini queries about how to tackle problems rising from 68% to 90%. Find out more →
DiffusionGemma is our new experimental open model with up to 4x faster output on dedicated GPUs. Instead of predicting word-by-word, it generates entire blocks of text simultaneously. This lets the model self-correct and format complex markdown in real time.
Find out more → goo.gle/4vG0xcI
Say hello, hola, 你好 to Gemini 3.5 Live Translate: our latest audio model built for fast, cross-language communication. 🌐
3.5 Live Translate can convert speech into over 70 languages and processes it as it’s streamed - while keeping tone, pace and pitch intact - allowing for more natural conversations.
We believe AI can be a dedicated research partner to help discover the next breakthrough. Enter Co-Scientist: our latest Gemini-based multi-agent system that can generate, debate and evolve novel hypotheses for complex scientific problems 🧵
Scientific discovery is a cycle of ideation, critique, and refinement. Co-Scientist mirrors this using a coalition of specialized Gemini-based agents leveraging its reasoning, multimodal, long-context and tool-use capabilities.
Our Gemini for Science tools could help scientists unlock their next breakthrough. 🧬
SynthID has already watermarked over 100 billion pieces of content, but transparency is a team sport. That’s why we’re partnering with @OpenAI, @ElevenLabs and Kakao to add SynthID watermarking to their models – accelerating the industry-wide momentum we started with @NVIDIA.
To date, SynthID verification in Gemini has been used 50+ million times to see if media was AI-generated. We’re now scaling this further by expanding content authentication directly into more everyday tools: Search and @GoogleChrome. So you can just ask: "Is this made with AI?"
We’re expanding our partnership with Singapore to help safely deploy AI at scale. 🇸🇬 Together with country experts, our new programs will focus on accelerating scientific discovery, advancing pandemic preparedness, and improving healthcare. Find out more →
